def getMetaData(explist):
# Get DataFrame of All Experiments
df_All = analysis.getAllExperiments()
# Get Cori Runs
df_Cori = df_All.loc[df_All['Experiment'].isin(explist)]
# Create Meta DataFrame
df_Cori_Meta = pd.DataFrame(
columns=['Workload', 'Ranks', 'Stencil', 'Runtime'])
# Loops Over All Cori Runs
for df in [df_Cori]:
for run in range(0, len(df)):
currentRun = df.iloc[run]
eid = currentRun['Experiment']
workload = currentRun['workload']
ranks = currentRun['processors']
stencil = currentRun['stencil_size']
rab_work = currentRun['rabbit_workload']
rid = currentRun['expid']
currentPath = './mlruns/' + str(eid) + '/' + str(
rid) + '/artifacts/bsp-trace.json'
# Print Progress
print(eid, currentPath)
# Check that Rabbit is Off
if (rab_work == 0):
# Get Data
currentData = analysis.getData(currentPath)
currentData = currentData[currentData['rank'] == 0]
# Calculate Total Runtime
currentRunTime = currentData['interval_max_usec'].sum(
) / 1000000
# Add to Metadata
df_Cori_Meta.loc[len(df_Cori_Meta)] = [
workload,
int(ranks),
int(stencil), currentRunTime
]
return df_Cori_Meta
def main():
expRange = list( range( 235, 330 ) ) + list( range( 450, 550 ) )
#writeMetaData( 'Results/AttawayData.csv', list( expRange ) )
#writeNormalizedMetaData( 'Results/AttawayData.csv', 'Results/AttawayNormalized.csv' )
#generateRuntimeFigure( 'Results/AttawayData.csv', 'Figures/AttawayRuntime.png' )
workloads = ['lammps']
#workloads = ['sleep', 'fwq', 'dgemm', 'spmv', 'hpcg', 'lammps']
df_All = analysis.getAllExperiments()
df_All = df_All.loc[ df_All[ 'Experiment' ].isin( expRange ) ]
CI = 0.90
baseRanks = 256
for workload in workloads:
generatePredictionFigure( df_All, workload, baseRanks, CI, 'Results/AttawayData.csv' )
# save data into a npy
np.save(fname, data)
return data
workloads = ['lammps']
#workloads=['sleep','fwq','dgemm','spmv','lammps','hpcg']
_FACTOR = 1000000
_ALPHA = 0.05
p = ((1.0 - (_ALPHA / 2.0)) * 100)
workload = workloads[0]
platform = 'Attaway'
df_All = analysis.getAllExperiments()
if platform == 'Cori':
coriRange = list(range(85, 235)) + list(range(330, 450))
df_platform = df_All.loc[df_All['Experiment'].isin(coriRange)]
df_runtimes = pd.read_csv(
'Results/CoriData.csv',
usecols=['Workload', 'Ranks', 'Stencil', 'Runtime'])
elif platform == 'Attaway':
attawayRange = list(range(235, 330)) + list(range(450, 550))
df_platform = df_All.loc[df_All['Experiment'].isin(attawayRange)]
df_runtimes = pd.read_csv(
'Results/AttawayData.csv',
usecols=['Workload', 'Ranks', 'Stencil', 'Runtime'])
else:
print('Error, unknown platform')